1. Field of the Invention
The present invention relates to an image sensing apparatus having a noise reduction circuit, and to a control method for such an image sensing apparatus. The present invention also relates to a storage medium storing a program for sensing an image of an object, which program is executed by a CPU of an image sensing apparatus.
2. Related Background Art
A conventional video camera has a noise reduction circuit for removing noise from a video signal. Noise reduction circuits, as well as various other video signal processing circuits, are now made of digital components along with the advent of digital video (DV) cassettes (SD format) and the like.
A cyclic type signal processing circuit, using a field memory, is generally used for a digital noise reduction circuit. As the price of memory is declining with time, digital noise reduction circuits also are being used for general video cameras in home use.
A cyclic type noise reduction circuit will be described which removes noise using field images having a correlation in time. As shown in FIG. 3, a cyclic noise reduction circuit has an input terminal 51, an adder 52, a subtractor 53, a multiplier 54, a field memory 55, a limiter 56 and an output terminal 57.
A signal Si input at the input terminal 51 is supplied to the adder 52 and subtractor 53. The subtractor 53 subtracts the signal Si from a signal Sf, where Sf is a delayed signal output by the field memory 55, to thereby detect a noise signal Sn1 between fields. The detected signal Sn1 output by the subtractor 53 is supplied to the limiter 56.
Motion components contained in the signal Sn1 are eliminated by the limiter 56, which outputs a signal Sn2. This signal Sn2 is multiplied by an externally supplied coefficient K (hereinafter called a cyclic coefficient) by the multiplier. This signal K·Sn2 is supplied to the adder 52.
The adder 52 adds the signal Si to the signal K·Sn2 to remove noise components from the signal Si. A signal So output from the adder 52 is supplied to the field memory 55 and also is output from the output terminal 57.
For simplification of description, it is assumed that Sn1=Sn2=Sn. The signal Sn is therefore given by the following equation:Sn=Sf−Si  (1)
The signal So is given by the following equation:So=Si+K·Sn =Si+K·(Sf−Si)=(1−K)·Si+K·Sf  (2)
As seen from the equation (2), a signal So having less noise components can be obtained as follows. Since the signal Si contains noise components and the signal Sf is a delayed signal corresponding to the signal So, from which noise components have been eliminated, the noise components become smaller as the cyclic coefficient K approaches the value 1. If the cyclic coefficient K is set to 0, the signal Si becomes the signal So.
The more effectively the noise components can be removed, the more the cyclic coefficient K can be made to approach the value 1. A video signal generated by a video camera is more likely to be affected by noise, because of high density mounting of small components, high speed digitalization, high speed signal processing, and high speed component control. In order to avoid this, it is required to set the amount of noise reduction larger.
However, if the amount of noise reduction is made larger, although the noise reduction effect is improved, influence of a preceding field upon a current field becomes larger. Therefore, a latent image of a scene having a moving object becomes conspicuous.
This problem also occurs when a zoom operation is performed because the size of an object changes between successive fields even if the object does not move.